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jajapy

Baum-Welch for all kind of Markov models

https://github.com/rapfff/jajapy

Science Score: 67.0%

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    CITATION.cff file
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    Found .zenodo.json file
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    DOI references
    Found 1 DOI reference(s) in README
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    Links to: arxiv.org, researchgate.net, springer.com
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    Scientific vocabulary similarity
    Low similarity (12.7%) to scientific vocabulary

Keywords

baum-welch hidden-markov-model machine-learning markov-chain markov-decision-processes markov-model model-checking python storm
Last synced: 6 months ago · JSON representation ·

Repository

Baum-Welch for all kind of Markov models

Basic Info
  • Host: GitHub
  • Owner: Rapfff
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 8.23 MB
Statistics
  • Stars: 21
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
  • Releases: 19
Topics
baum-welch hidden-markov-model machine-learning markov-chain markov-decision-processes markov-model model-checking python storm
Created over 3 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License Citation

README.md


[![Pypi](https://img.shields.io/pypi/v/jajapy)](https://pypi.org/project/jajapy/) [![Python 3.6](https://img.shields.io/badge/python-3.6%2B-blue)](https://www.python.org/downloads/release/python-360/) ![PyPI - Wheel](https://img.shields.io/pypi/wheel/aalpy) [![License](https://img.shields.io/github/license/Rapfff/jajapy)](https://en.wikipedia.org/wiki/MIT_License)

Introduction

jajapy is a python library implementing the Baum-Welch algorithm on various kinds of Markov models. jajapy generates models which are compatible with the Stormpy model checker. Thus, jajapycan be use as a learning extension to the Storm model checker.

Main features

jajapy provides:

| Markov Model | Learning Algorithm(s) | |-------|:-------------:| | MC | Baum-Welch for MCs
Alergia ([ref](https://www.researchgate.net/publication/2543721_Learning_Stochastic_Regular_Grammars_by_Means_of_a_State_Merging_Method/stats)) | | MDP | Baum-Welch for MDPs ([ref](https://arxiv.org/abs/2110.03014))
Active Baum-Welch ([ref](https://arxiv.org/abs/2110.03014))
IOAlergia ([ref](https://link.springer.com/content/pdf/10.1007/s10994-016-5565-9.pdf))| | CTMC | Baum-Welch for CTMCs
Baum-Welch for synchronous compositions of CTMCs| | PCTMC | Baum-Welch for PCTMCs ([ref](https://arxiv.org/abs/2302.08588))| | HMM | Baum-Welch for HMMs ([ref](https://web.ece.ucsb.edu/Faculty/Rabiner/ece259/Reprints/tutorial%20on%20hmm%20and%20applications.pdf)) | | GoHMM | Baum-Welch for GoHMMs ([ref](http://www.inass.org/2020/2020022920.pdf)) |

jajapy is compatible with Prism and Storm.

Installation

pip install jajapy

Requirements

Documentation

Available on readthedoc

Reference and citation

  • The extended version of the tool paper presented at QEST'23 is available here
  • If you use this tool in your research, please cite it

About the author

My website

Owner

  • Name: Raphaël
  • Login: Rapfff
  • Kind: user
  • Location: Iceland
  • Company: Reykjavík University

PhD student at Reykjavik University

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Reynouard"
  given-names: "Raphaël"
title: "jajapy"
version: 0.10
date-released: 2023-03-01
url: "https://github.com/Rapfff/jajapy"
license: MIT

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Dependencies

requirements.txt pypi
  • numpy *
  • scipy *
setup.py pypi
  • numpy *
  • scipy *